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Mistral-7B-Instruct-v0.2-MI-1e-6

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the princeton-nlp/mistral-instruct-ultrafeedback dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5092
  • Rewards/chosen: -0.5707
  • Rewards/rejected: -0.6483
  • Rewards/accuracies: 0.5931
  • Rewards/margins: 0.0775
  • Logps/rejected: -0.6483
  • Logps/chosen: -0.5707
  • Logits/rejected: -3.4481
  • Logits/chosen: -3.4530

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-06
  • train_batch_size: 2
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
1.46 0.8573 400 1.5092 -0.5707 -0.6483 0.5931 0.0775 -0.6483 -0.5707 -3.4481 -3.4530

Framework versions

  • Transformers 4.42.0
  • Pytorch 2.1.2+cu121
  • Datasets 2.14.6
  • Tokenizers 0.19.1
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